Innovative Research on Translation Quality Assessment Models in the New Era

Yu Zhu

doi:doi:10.11648/j.hss.20231105.12

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Innovative Research on Translation Quality Assessment Models in the New Era

Yu Zhu

Published in Humanities and Social Sciences (Volume 11, Issue 5)

Received: 12 September 2023 Accepted: 20 October 2023 Published: 31 October 2023

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Abstract

With the deepening of economic globalization, the significance of translation services in economic, cultural, and technological domains has become increasingly pronounced. Yet, determining how to evaluate the quality of translations and ensure their precision and reliability remains a central concern for both the academic and professional realms of translation. This paper offers an in-depth exploration of current models of translation quality assessment, highlighting their limitations, such as restricted applicability, underutilization of technology, absence of standardized evaluation criteria, and some models being excessively theoretical. To address these challenges, this article, integrating insights from contemporary technology and market demands, proposes innovative perspectives and methodologies to bolster translation quality assessment models from various angles. This encompasses refining assessment models from a multifaceted viewpoint, leveraging cutting-edge technology to enhance evaluation outcomes, expediting the dissemination and application of these models, accelerating the establishment of translation corpus resources, and advancing translation quality assessment tools. Furthermore, with the evolution of artificial intelligence and machine learning technologies, methods and tools for translation quality assessment are also continuously advancing. This paper delves into how to synergize these state-of-the-art technologies to elevate the accuracy and efficiency of translation quality evaluation. By contrasting different assessment methodologies, this article aims to provide a comprehensive guide for translators and researchers, assisting them in selecting the evaluation tools and methods best suited to their needs. In essence, this research seeks to furnish novel insights for the optimization of translation quality assessment models, further driving the progression of translation quality evaluation practices.

Published in	Humanities and Social Sciences (Volume 11, Issue 5)
DOI	10.11648/j.hss.20231105.12
Page(s)	176-181
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Translation Quality Assessment, Assessment Model Innovation, Translation Technology

References

[1]	J. House, A Model for Translation Quality Assessment [M]. Tübingen: Narr, 1977.
[2]	K. Reiss, Translation Criticism: The Potential and Limitations [M]. Manchester: St. Jerome, 2000.
[3]	M. Williams, Translation Quality Assessment: An Argumentation-Centered Approach [M]. Ottawa: University of Ottawa Press, 2004.
[4]	He San Ning. Research on Translation Quality Assessment Models [M]. Beijing: Central Compilation & Translation Press, 2015.
[5]	Wang Shao Shuang. A New Perspective on Translation Quality Research - A Review of "Quality in Professional Translation: Assessment and Improvement" [J]. Foreign Languages (Journal of Shanghai International Studies University), 2017 (1): 108-112.
[6]	C. Angelelli, & H. Jacobson. Testing and Assessment in Translation and Interpreting Studies [C]. Amsterdam: John Benjamins, 2009.
[7]	I. Depraetere, Perspectives on Translation Quality [C]. Berlin: De Gruyter Mouton, 2011.
[8]	Wu Xinxian, Li Hong’an. Preliminary Exploration on Equivalent Translation [J]. Foreign Language Teaching and Research, 1984 (3): 2-10.
[9]	Fan Shouyi. Fuzzy Mathematics and Translation Evaluation [J]. Chinese Translation, 1987 (4): 2-9.
[10]	Gu Zhengkun. On the Multi-faceted Complementary Theories of Translation Standards [J]. Beijing Social Sciences, 1989 (1): 71-78.
[11]	Hou Guojin. Pragmatic Marking Theory and its Application: A New Approach to Translation Evaluation [M]. Chengdu: Sichuan University Press, 2005.
[12]	Si Xianzhu. Functional Linguistics and Translation Studies: Constructing a Translation Quality Evaluation Model [M]. Beijing: Peking University Press, 2007.
[13]	He Sanning. Re-exploring Parameters for Translation Quality Evaluation [J]. Chinese Translation, 2012 (2): 27-31.
[14]	Wang Junsong. A New Direction in Translation Quality Evaluation: DQF Dynamic Quality Evaluation Framework [J]. Chinese Science and Technology Translation, 2019 (3): 27-29.
[15]	Wang Qing, Ma Xiao. Research on Machine Translation Quality Evaluation Methods from the Perspective of Problem Awareness [J]. Hunan Social Sciences, 2020 (6): 144-151.
[16]	Dai Guangrong, Zuo Shangjun. The Use and Research of Corpora in Translation Quality Evaluation [J]. Foreign Language Teaching, 2021 (2): 92-96.

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APA Style

Yu Zhu. (2023). Innovative Research on Translation Quality Assessment Models in the New Era. Humanities and Social Sciences, 11(5), 176-181. https://doi.org/10.11648/j.hss.20231105.12

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ACS Style

Yu Zhu. Innovative Research on Translation Quality Assessment Models in the New Era. Humanit. Soc. Sci. 2023, 11(5), 176-181. doi: 10.11648/j.hss.20231105.12

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AMA Style

Yu Zhu. Innovative Research on Translation Quality Assessment Models in the New Era. Humanit Soc Sci. 2023;11(5):176-181. doi: 10.11648/j.hss.20231105.12

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@article{10.11648/j.hss.20231105.12,
  author = {Yu Zhu},
  title = {Innovative Research on Translation Quality Assessment Models in the New Era},
  journal = {Humanities and Social Sciences},
  volume = {11},
  number = {5},
  pages = {176-181},
  doi = {10.11648/j.hss.20231105.12},
  url = {https://doi.org/10.11648/j.hss.20231105.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.hss.20231105.12},
  abstract = {With the deepening of economic globalization, the significance of translation services in economic, cultural, and technological domains has become increasingly pronounced. Yet, determining how to evaluate the quality of translations and ensure their precision and reliability remains a central concern for both the academic and professional realms of translation. This paper offers an in-depth exploration of current models of translation quality assessment, highlighting their limitations, such as restricted applicability, underutilization of technology, absence of standardized evaluation criteria, and some models being excessively theoretical. To address these challenges, this article, integrating insights from contemporary technology and market demands, proposes innovative perspectives and methodologies to bolster translation quality assessment models from various angles. This encompasses refining assessment models from a multifaceted viewpoint, leveraging cutting-edge technology to enhance evaluation outcomes, expediting the dissemination and application of these models, accelerating the establishment of translation corpus resources, and advancing translation quality assessment tools. Furthermore, with the evolution of artificial intelligence and machine learning technologies, methods and tools for translation quality assessment are also continuously advancing. This paper delves into how to synergize these state-of-the-art technologies to elevate the accuracy and efficiency of translation quality evaluation. By contrasting different assessment methodologies, this article aims to provide a comprehensive guide for translators and researchers, assisting them in selecting the evaluation tools and methods best suited to their needs. In essence, this research seeks to furnish novel insights for the optimization of translation quality assessment models, further driving the progression of translation quality evaluation practices.
},
 year = {2023}
}

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TY  - JOUR
T1  - Innovative Research on Translation Quality Assessment Models in the New Era
AU  - Yu Zhu
Y1  - 2023/10/31
PY  - 2023
N1  - https://doi.org/10.11648/j.hss.20231105.12
DO  - 10.11648/j.hss.20231105.12
T2  - Humanities and Social Sciences
JF  - Humanities and Social Sciences
JO  - Humanities and Social Sciences
SP  - 176
EP  - 181
PB  - Science Publishing Group
SN  - 2330-8184
UR  - https://doi.org/10.11648/j.hss.20231105.12
AB  - With the deepening of economic globalization, the significance of translation services in economic, cultural, and technological domains has become increasingly pronounced. Yet, determining how to evaluate the quality of translations and ensure their precision and reliability remains a central concern for both the academic and professional realms of translation. This paper offers an in-depth exploration of current models of translation quality assessment, highlighting their limitations, such as restricted applicability, underutilization of technology, absence of standardized evaluation criteria, and some models being excessively theoretical. To address these challenges, this article, integrating insights from contemporary technology and market demands, proposes innovative perspectives and methodologies to bolster translation quality assessment models from various angles. This encompasses refining assessment models from a multifaceted viewpoint, leveraging cutting-edge technology to enhance evaluation outcomes, expediting the dissemination and application of these models, accelerating the establishment of translation corpus resources, and advancing translation quality assessment tools. Furthermore, with the evolution of artificial intelligence and machine learning technologies, methods and tools for translation quality assessment are also continuously advancing. This paper delves into how to synergize these state-of-the-art technologies to elevate the accuracy and efficiency of translation quality evaluation. By contrasting different assessment methodologies, this article aims to provide a comprehensive guide for translators and researchers, assisting them in selecting the evaluation tools and methods best suited to their needs. In essence, this research seeks to furnish novel insights for the optimization of translation quality assessment models, further driving the progression of translation quality evaluation practices.

VL  - 11
IS  - 5
ER  -

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Author Information

Yu Zhu

School of Foreign Language, Liaoning University of International Business and Economics, Dalian, China

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Plain Text BibTeX RIS

APA Style

Yu Zhu. (2023). Innovative Research on Translation Quality Assessment Models in the New Era. Humanities and Social Sciences, 11(5), 176-181. https://doi.org/10.11648/j.hss.20231105.12

Copy | Download

ACS Style

Yu Zhu. Innovative Research on Translation Quality Assessment Models in the New Era. Humanit. Soc. Sci. 2023, 11(5), 176-181. doi: 10.11648/j.hss.20231105.12

Copy | Download

AMA Style

Yu Zhu. Innovative Research on Translation Quality Assessment Models in the New Era. Humanit Soc Sci. 2023;11(5):176-181. doi: 10.11648/j.hss.20231105.12

Copy | Download

@article{10.11648/j.hss.20231105.12,
  author = {Yu Zhu},
  title = {Innovative Research on Translation Quality Assessment Models in the New Era},
  journal = {Humanities and Social Sciences},
  volume = {11},
  number = {5},
  pages = {176-181},
  doi = {10.11648/j.hss.20231105.12},
  url = {https://doi.org/10.11648/j.hss.20231105.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.hss.20231105.12},
  abstract = {With the deepening of economic globalization, the significance of translation services in economic, cultural, and technological domains has become increasingly pronounced. Yet, determining how to evaluate the quality of translations and ensure their precision and reliability remains a central concern for both the academic and professional realms of translation. This paper offers an in-depth exploration of current models of translation quality assessment, highlighting their limitations, such as restricted applicability, underutilization of technology, absence of standardized evaluation criteria, and some models being excessively theoretical. To address these challenges, this article, integrating insights from contemporary technology and market demands, proposes innovative perspectives and methodologies to bolster translation quality assessment models from various angles. This encompasses refining assessment models from a multifaceted viewpoint, leveraging cutting-edge technology to enhance evaluation outcomes, expediting the dissemination and application of these models, accelerating the establishment of translation corpus resources, and advancing translation quality assessment tools. Furthermore, with the evolution of artificial intelligence and machine learning technologies, methods and tools for translation quality assessment are also continuously advancing. This paper delves into how to synergize these state-of-the-art technologies to elevate the accuracy and efficiency of translation quality evaluation. By contrasting different assessment methodologies, this article aims to provide a comprehensive guide for translators and researchers, assisting them in selecting the evaluation tools and methods best suited to their needs. In essence, this research seeks to furnish novel insights for the optimization of translation quality assessment models, further driving the progression of translation quality evaluation practices.
},
 year = {2023}
}

Copy | Download

TY  - JOUR
T1  - Innovative Research on Translation Quality Assessment Models in the New Era
AU  - Yu Zhu
Y1  - 2023/10/31
PY  - 2023
N1  - https://doi.org/10.11648/j.hss.20231105.12
DO  - 10.11648/j.hss.20231105.12
T2  - Humanities and Social Sciences
JF  - Humanities and Social Sciences
JO  - Humanities and Social Sciences
SP  - 176
EP  - 181
PB  - Science Publishing Group
SN  - 2330-8184
UR  - https://doi.org/10.11648/j.hss.20231105.12
AB  - With the deepening of economic globalization, the significance of translation services in economic, cultural, and technological domains has become increasingly pronounced. Yet, determining how to evaluate the quality of translations and ensure their precision and reliability remains a central concern for both the academic and professional realms of translation. This paper offers an in-depth exploration of current models of translation quality assessment, highlighting their limitations, such as restricted applicability, underutilization of technology, absence of standardized evaluation criteria, and some models being excessively theoretical. To address these challenges, this article, integrating insights from contemporary technology and market demands, proposes innovative perspectives and methodologies to bolster translation quality assessment models from various angles. This encompasses refining assessment models from a multifaceted viewpoint, leveraging cutting-edge technology to enhance evaluation outcomes, expediting the dissemination and application of these models, accelerating the establishment of translation corpus resources, and advancing translation quality assessment tools. Furthermore, with the evolution of artificial intelligence and machine learning technologies, methods and tools for translation quality assessment are also continuously advancing. This paper delves into how to synergize these state-of-the-art technologies to elevate the accuracy and efficiency of translation quality evaluation. By contrasting different assessment methodologies, this article aims to provide a comprehensive guide for translators and researchers, assisting them in selecting the evaluation tools and methods best suited to their needs. In essence, this research seeks to furnish novel insights for the optimization of translation quality assessment models, further driving the progression of translation quality evaluation practices.

VL  - 11
IS  - 5
ER  -

Copy | Download